Powered by OpenAIRE graph
Found an issue? Give us feedback

Axeon Ltd

2 Projects, page 1 of 1
  • Funder: UK Research and Innovation Project Code: EP/K002252/1
    Funder Contribution: 5,621,020 GBP

    The UK electricity system faces challenges of unprecedented proportions. It is expected that 35 to 40% of the UK electricity demand will be met by renewable generation by 2020, an order of magnitude increase from the present levels. In the context of the targets proposed by the UK Climate Change Committee it is expected that the electricity sector would be almost entirely decarbonised by 2030 with significantly increased levels of electricity production and demand driven by the incorporation of heat and transport sectors into the electricity system. The key concerns are associated with system integration costs driven by radical changes on both the supply and the demand side of the UK low-carbon system. Our analysis to date suggests that a low-carbon electricity future would lead to a massive reduction in the utilisation of conventional electricity generation, transmission and distribution assets. The large-scale deployment of energy storage could mitigate this reduction in utilisation, producing significant savings. In this context, the proposed research aims at (i) developing novel approaches for evaluating the economic and environmental benefits of a range of energy storage technologies that could enhance efficiency of system operation and increase asset utilization; and (ii) innovation around 4 storage technologies; Na-ion, redox flow batteries (RFB), supercapacitors, and thermal energy storage (TES). These have been selected because of their relevance to grid-scale storage applications, their potential for transformative research, our strong and world-leading research track record on these topics and UK opportunities for exploitation of the innovations arising. At the heart of our proposal is a whole systems approach, recognising the need for electrical network experts to work with experts in control, converters and storage, to develop optimum solutions and options for a range of future energy scenarios. This is essential if we are to properly take into account constraints imposed by the network on the storage technologies, and in return limitations imposed by the storage technologies on the network. Our work places emphasis on future energy scenarios relevant to the UK, but the tools, methods and technologies we develop will have wide application. Our work will provide strategic insights and direction to a wide range of stakeholders regarding the development and integration of energy storage technologies in future low carbon electricity grids, and is inspired by both (i) limitations in current grid regulation, market operation, grid investment and control practices that prevent the role of energy storage being understood and its economic and environmental value quantified, and (ii) existing barriers to the development and deployment of cost effective energy storage solutions for grid application. Key outputs from this programme will be; a roadmap for the development of grid scale storage suited to application in the UK; an analysis of policy options that would appropriately support the deployment of storage in the UK; a blueprint for the control of storage in UK distribution networks; patents and high impact papers relating to breakthrough innovations in energy storage technologies; new tools and techniques to analyse the integration of storage into low carbon electrical networks; and a cohort of researchers and PhD students with the correct skills and experience needed to support the future research, development and deployment in this area.

    more_vert
  • Funder: UK Research and Innovation Project Code: EP/I038586/1
    Funder Contribution: 3,012,030 GBP

    Hybrid electric vehicles (HEV) are far more complex than conventional vehicles. There are numerous challenges facing the engineer to optimise the design and choice of system components as well as their control systems. At the component level there is a need to obtain a better understanding of the basic science/physics of new subsystems together with issues of their interconnectivity and overall performance at the system level. The notion of purpose driven models requires models of differing levels of fidelity, e.g. control, diagnostics and prognostics. Whatever the objective of these models, they will differ from detailed models which will provide a greater insight and understanding at the component level. Thus there is a need to develop a systematic approach resulting in a set of guidelines and tools which will be of immense value to the design engineer in terms of best practice. The Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles (FUTURE) consortium will address the above need for developing tools and methodologies. A systematic and unified approach towards component level modelling will be developed, underpinned by a better understanding of the fundamental science of the essential components of a FUTURE hybrid electrical vehicle. The essential components will include both energy storage devices (fuel cells, batteries and ultra-capacitors) and energy conversion devices (electrical machine drives and power electronics). Detailed mathematical models will be validated against experimental data over their full range of operation, including the extreme limits of performance. Reduced order lumped parameter models are then to be derived and verified against these validated models, with the level of fidelity being defined by the purpose for which the model is to be employed. The work will be carried out via three inter-linked work packages, each having two sub-work packages. WP1 will address the detailed component modelling for the energy storage devices, WP2 will address the detailed component modelling for the energy conversion devices and WP3 will address reduced order modelling and control optimisation. The tasks will be carried out iteratively from initial component level models from WP1 and WP2 to WP3, subsequent reduced order models developed and verified against initial models, and banks of linear-time invariant models developed for piecewise control optimisation. Additionally, models of higher fidelity are to be obtained for the purpose of on-line diagnosis. The higher fidelity models will be able to capture the transient conditions which may contain information on the known failure modes. In addition to optimising the utility of healthy components in their normal operating ranges, to ensure maximum efficiency and reduced costs, further optimisation, particularly at the limits of performance where component stress applied in a controlled manner is considered to be potentially beneficial, the impact of ageing and degradation is to be assessed. Methodologies for prognostics developed in other industry sectors, e.g. aerospace, nuclear, will be reviewed for potential application and/or tailoring for purpose. Models for continuous component monitoring for the purpose of prognosis will differ from those for control and diagnosis, and it is envisaged that other non-parametric feature-based models and techniques for quantification of component life linked to particular use-case scenarios will be required to be derived. All members of the consortia have specific individual roles as well as cross-discipline roles and interconnected collaborative activities. The multi-disciplinary nature of the proposed team will ensure that the outputs and outcomes of this consortia working in close collaboration with an Industrial Advisory Committee will deliver research solutions to the HEV issues identified.

    more_vert

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

Content report
No reports available
Funder report
No option selected
arrow_drop_down

Do you wish to download a CSV file? Note that this process may take a while.

There was an error in csv downloading. Please try again later.